Structure-based Virtual Screening Approach Research Articles

Discovery of P2Y2 Receptor Antagonist Scaffolds through Virtual High-Throughput Screening.

The human ATP- and UTP-activated P2Y2 receptor (P2Y2R) is a Gq protein-coupled receptor involved in several pathophysiological conditions including acute and chronic inflammation, cancer, and pain. Despite its potential as a novel drug target, only few P2Y2R antagonists have been developed so far, all of which suffer from severe drawbacks. These include (i) high polarity due to one or several negative charges resulting in low oral bioavailability, (ii) metabolic instability and generally poor pharmacokinetic properties, and/or (iii) lack of selectivity, which limits their utility for in vitro and in vivo studies aimed at target validation. In search of new druglike scaffolds for P2Y2R antagonists, we employed a structure-based virtual high-throughput screening approach utilizing the complex of a P2Y2R homology model with one of the most potent and selective orthosteric antagonists described so far, AR-C118925 (10). After virtual screening of 3.2 million molecules, 58 compounds were purchased and pharmacologically evaluated. Several novel antagonist scaffolds were discovered, and their binding modes at the human P2Y2R were analyzed by molecular docking studies. The investigated antagonists likely share a similar binding mode with 10 which includes accommodation of bulky, lipophilic groups in the putative orthosteric binding site of the P2Y2R. The discovered scaffolds and the elucidated structure-activity relationships provide a basis for the development of future drug candidates for the P2Y2R which have great potential as novel drugs.

Identification of a dual FLT3 and MNK2 inhibitor for acute myeloid leukemia treatment using a structure-based virtual screening approach

Fms-like tyrosine kinase 3 (FLT3) is considered a promising therapeutic target for acute myeloid leukemia (AML) in the clinical. However, monotherapy with FLT3 inhibitor is usually accompanied by drug resistance. Dual inhibitors might be therapeutically beneficial to patients with AML due to their ability to overcome drug resistance. Mitogen-activated protein kinase (MAPK)-interacting kinases (MNKs) phosphorylate eukaryotic translation initiation factor 4E (eIF4E), which brings together the RAS/RAF/ERK and PI3K/AKT/mTOR oncogenic pathways. Therefore, dual inhibition of FLT3 and MNK2 might have an additive effect against AML. Herein, a structure-based virtual screening approach was performed to identify dual inhibitors of FLT3 and MNK2 from the ChemDiv database. Compound K783-0308 was identified as a dual inhibitor of FLT3 and MNK2 with IC50 values of 680 and 406 nM, respectively. In addition, the compound showed selectivity for both FLT3 and MNK2 in a panel of 82 kinases. The structure-activity relationship analysis and common interactions revealed interactions between K783-0308 analogs and FLT3 and MNK2. Furthermore, K783-0308 inhibited MV-4-11 and MOLM-13 AML cell growth and induced G0/G1 cell cycle arrest. Taken together, the dual inhibitor K783-0308 showed promising results and can be potentially optimized as a lead compound for AML treatment.

Multi-stage structure-based virtual screening approach towards identification of potential SARS-CoV-2 NSP13 helicase inhibitors

On account of its crucial role in the virus life cycle, SARS-COV-2 NSP13 helicase enzyme was exploited as a promising target to identify a novel potential inhibitor using multi-stage structure-based drug discovery approaches. Firstly, a 3D pharmacophore was generated based on the collected data from a protein-ligand interaction fingerprint (PLIF) study using key interactions between co-crystallised fragments and the NSP13 helicase active site. The ZINC database was screened through the generated 3D-pharmacophore retrieving 13 potential hits. All the retrieved hits exceeded the benchmark score of the co-crystallised fragments at the molecular docking step and the best five-hit compounds were selected for further analysis. Finally, a combination between molecular dynamics simulations and MM-PBSA based binding free energy calculations was conducted on the best hit (compound FWM-1) bound to NSP13 helicase enzyme, which identified FWM-1 as a potential potent NSP13 helicase inhibitor with binding free energy equals −328.6 ± 9.2 kcal/mol.

Virus-host interaction analysis in colorectal cancer identifies core virus network signature and small molecules

Colorectal cancer (CRC) is a significant contributor to cancer-related deaths caused by an unhealthy lifestyle. Multiple studies reveal that viruses are involved in colorectal tumorigenesis. The viruses such as Human Cytomegalovirus (HCMV), Human papillomaviruses (HPV16 & HPV18), and John Cunningham virus (JCV) are known to cause colorectal cancer. The molecular mechanisms of cancer genesis and maintenance shared by these viruses remain unclear. We analysed the virus-host networks and connected them with colorectal cancer proteome datasets and extracted the core shared interactions in the virus-host CRC network. Our network topology analysis identified prominent virus proteins RL6 (HCMV), VE6 (HPV16 and HPV18), and Large T antigen (JCV). Sequence analysis uncovered short linear motifs (SLiMs) in each viral target. We used these targets to identify the antiviral drugs through a structure-based virtual screening approach. This analysis highlighted that temsavir, pimodivir, famotine, and bictegravir bind to each virus protein target, respectively. We also assessed the effect of drug binding using molecular dynamic simulations, which shed light on the modulatory effect of drug molecules on SLiM regions in viral targets. Hence, our systematic screening of virus-host networks revealed viral targets, which could be crucial for cancer therapy.

Identification and analysis of a selective DYRK1A inhibitor

The dysregulation of DYRK1A is implicated in many diseases such as cancer, diabetes, and neurodegenerative diseases. Alzheimer’s disease is one of the most common neurodegenerative disease and has elevated interest in DYRK1A research. Overexpression of DYRK1A has been linked to the formation of tau aggregates. Currently, an effective therapeutic treatment that targets DYRK1A is lacking. A specific small-molecule inhibitor would further our understanding of the physiological role of DYRK1A in neurodegenerative diseases and could be presented as a possible therapeutic option. In this study, we identified pharmacological interactions within the DYRK1A active site and performed a structure-based virtual screening approach to identify a selective small-molecule inhibitor. Several compounds were selected in silico for enzymatic and cellular assays, yielding a novel inhibitor. A structure-activity relationship analysis was performed to identify areas of interactions for the compounds selected in this study. When tested in vitro, reduction of DYRK1A dependent phosphorylation of tau was observed for active compounds. The active compounds also improved tau turbidity, suggesting that these compounds could alleviate aberrant tau aggregation. Testing the active compound against a panel of kinases across the kinome revealed greater selectivity towards DYRK1A. Our study demonstrates a serviceable protocol that identified a novel and selective DYRK1A inhibitor with potential for further study in tau-related pathologies.

In silico Screening of Natural Phytocompounds Towards Identification of Potential Lead Compounds to Treat COVID-19.

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and Mpro through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed −12.0 and −10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against Mpro was found to be −9.7 and −8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for Mpro were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.

Hampering the early aggregation of PrP-E200K protein by charge-based inhibitors: a computational study

A multilayered computational workflow was designed to identify a druggable binding site on the surface of the E200K pathogenic mutant of the human prion protein, and to investigate the effect of the binding of small molecules in the inhibition of the early aggregation of this protein. At this purpose, we developed an efficient computational tool to scan the molecular interaction properties of a whole MD trajectory, thus leading to the characterization of plausible binding regions on the surface of PrP-E200K. These structural data were then employed to drive structure-based virtual screening and fragment-based approaches to the seeking of small molecular binders of the PrP-E200K. Six promising compounds were identified, and their binding stabilities were assessed by MD simulations. Therefore, analyses of the molecular electrostatic potential similarity between the bound complexes and unbound protein evidenced their potential activity as charged-based inhibitors of the PrP-E200K early aggregation.

Discovery of a Potent and Selective Chikungunya Virus Envelope Protein Inhibitor through Computer-Aided Drug Design

The worldwide expansion of chikungunya virus (CHIKV) into tropical and subtropical areas in the last 15 years has posed a currently unmet need for vaccines and therapeutics. The E2-E1 envelope glycoprotein complex binds receptors on the host cell and promotes membrane fusion during CHIKV entry, thus constituting an attractive target for the development of antiviral drugs. In order to identify CHIKV antivirals acting through inhibition of the envelope glycoprotein complex function, our first approach was to search for amenable druggable sites within the E2-E1 heterodimer. We identified a pocket located in the interface between E2 and E1 around the fusion loop. Then, via a structure-based virtual screening approach and in vitro assay of antiviral activity, we identified compound 7 as a specific inhibitor of CHIKV. Through a lead optimization process, we obtained compound 11 that demonstrated increased antiviral activity and low cytotoxicity (EC50 1.6 μM, CC50 56.0 μM). Molecular dynamics simulations were carried out and described a possible interaction pattern of compound 11 and the E1-E2 dimer that could be useful for further optimization. As expected from target site selection, compound 11 inhibited virus internalization during CHIKV entry. In addition, virus populations resistant to compound 11 included mutation E2-P173S, which mapped to the proposed binding pocket, and second site mutation E1-Y24H. Construction of recombinant viruses showed that these mutations conferred antiviral resistance in the parental background. Finally, compound 11 presents acceptable solubility values and is chemically and enzymatically stable in different media. Altogether, these findings uncover a suitable pocket for the design of CHIKV entry inhibitors with promising antiviral activity and pharmacological profiles.

Identification of Kaurane-Type Diterpenes as Inhibitors of Leishmania Pteridine Reductase I.

The current treatments against Leishmania parasites present high toxicity and multiple side effects, which makes the control and elimination of leishmaniasis challenging. Natural products constitute an interesting and diverse chemical space for the identification of new antileishmanial drugs. To identify new drug options, an in-house database of 360 kauranes (tetracyclic diterpenes) was generated, and a combined ligand- and structure-based virtual screening (VS) approach was performed to select potential inhibitors of Leishmania major (Lm) pteridine reductase I (PTR1). The best-ranked kauranes were employed to verify the validity of the VS approach through LmPTR1 enzyme inhibition assay. The half-maximal inhibitory concentration (IC50) values of selected bioactive compounds were examined using the random forest (RF) model (i.e., 2β-hydroxy-menth-6-en-5β-yl ent-kaurenoate (135) and 3α-cinnamoyloxy-ent-kaur-16-en-19-oic acid (302)) were below 10 μM. A compound similar to 302, 3α-p-coumaroyloxy-ent-kaur-16-en-19-oic acid (302a), was also synthesized and showed the highest activity against LmPTR1. Finally, molecular docking calculations and molecular dynamics simulations were performed for the VS-selected, most-active kauranes within the active sites of PTR1 hybrid models, generated from three Leishmania species that are known to cause cutaneous leishmaniasis in the new world (i.e., L. braziliensis, L. panamensis, and L. amazonensis) to explore the targeting potential of these kauranes to other species-dependent variants of this enzyme.

Meticulous assessment of natural compounds from NPASS database for identifying analogue of GRL0617, the only known inhibitor for SARS-CoV2 papain-like protease (PLpro) using rigorous computational workflow.

The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV’s. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.Graphic abstract

Optimizing Bedaquiline for cardiotoxicity by structure based virtual screening, DFT analysis and molecular dynamic simulation studies to identify selective MDR-TB inhibitors

The online version contains supplementary material available at 10.1007/s40203-021-00086-x.

Identification of Phelligridin-Based Compounds as Novel Human CD73 Inhibitors.

As an emerging immune checkpoint, CD73 has received more attention in the past decade. Inhibition of CD73 enzymatic activity can enhance antitumor immunity. Several CD73 inhibitors have been identified by in vitro assays in recent years, but they remain premature for clinical application, indicating that more novel CD73 inhibitors should be studied. Herein, we aimed to identify novel CD73 inhibitors that hopefully are suitable drug candidates by using computer-aided drug discovery and enzymatic-based assays. Five-hundred molecules with high binding affinity were retrieved from the Chemdiv-Plus database by using a structure-based virtual screening approach. Then, we analyzed the drug properties of these molecules and obtained 68 small molecules based on the oral noncentral nervous system (CNS) drug profile. The inhibition rates of these molecules against CD73 enzymatic activities were determined at a concentration of 100 μM, and 20 molecules had an inhibition rate greater than 20%, eight of which were dose-dependent, with IC50 values of 6.72-172.1 μM. Among the screening hits, phelligridin-based compounds had the best experimental inhibition values. Modeling studies indicate that the phelligridin group is sandwiched by the rings of F417 and F500 residues. The identified inhibitors have a molecular weight of approximately 500 Dal and are predicted to form primarily hydrogen bonds with CD73 in addition to hydrophobic stacking interactions. In conclusion, novel inhibitors with satisfactory drug properties may serve as lead compounds for the development of CD73-targeting drugs, and the binding modes may provide insight for phelligridin-based drug design.

Potential modulating effect of the Ascaris suum nicotinic acetylcholine receptor (nAChR) by compounds GSK575594A, diazepam and flumazenil discovered by structure-based virtual screening approach

Parasitic infections are a widespread health problem and research of novel anthelmintic compounds is of the utmost importance. In this study we performed a virtual screening campaign by coupling ligand-based pharmacophore, homology modeling and molecular docking. The virtual screening campaign was conducted using a joined pool of the Drugbank database and a library of purchasable compounds in order to identify drug like compounds with similar pharmacological activity. Our aim was to identify compounds with a potential antihelmintic modulatory effect on nicotinic acetylcholine receptors (nAChR). We derived a 3D pharmacophore model based on the chemical features of known Ascaris suum nAChR modulators. To evaluate the in silico predictions, we tested selected hit compounds in contraction assays using somatic muscle flaps of the Ascaris suum neuromuscular tissue. We tested the modulatory effects of GSK575594A, diazepam and flumazenil hit compounds on nematode contractions induced by acetyl choline (ACh). The compound GSK575594A (3 μM) increased the Emax by 21 % with the EC50 dose ratio of 0.96. Diazepam (100 μM) decreased the Emax by 15 % (1.11 g to 0.95 g) with the EC50 ratio of 1.42 (shifted to the left from 11.25 to 7.93). Flumazenil decreased the EC50 value (from 11.22 μM to 4.88 μM) value showing dose ratio of 2.30, and increased the Emax by 4 % (from 1.54 g to 1.59 g). The observed biological activity was rationalized by molecular docking calculations. Docking scores were calculated against several binding sites within the Ascaris suum homology model. We constructed the homology model using the ACR-16 subunit sequence. The compound GSK575594A showed strong affinity for the intersubunit allosteric binding site within the nAChR transmembrane domain. The binding modes of diazepam and flumazenil suggest that these compounds have a comparable affinity for orthosteric and allosteric nAChR binding sites. The selected hit compounds displayed potential for further optimization as lead compounds. Therefore, such compounds may be useful in neutralizing the growing resistance of parasites to drugs, either alone or in combination with existing conventional anthelmintics.

Identification of novel potential cyclooxygenase-2 inhibitors using ligand- and structure-based virtual screening approaches

Cyclooxygenase 2 (COX-2) is a well-established target for the design of anti-inflammatory intermediates. Celecoxib was selected as a template molecule to perform ligand-based virtual screening, i.e. to search for structures with similarity in shape and electrostatic potential, with a gradual increase in accuracy through the combined fitting of several steps using eight commercial databases. The molecules ZINC408709 and ZINC2090319 reproduced values within the limits established in an initial study of absorption and distribution in the body. No alert was fired for possible toxic groups when these molecules were subjected to toxicity prediction. Molecular docking results with these compounds showed a higher binding affinity in comparison to rofecoxib for the COX-2 target. Additionally, ZINC408709 and ZINC2090319 were predicted to be potentially biologically active. In in silico prediction of endocrine disruption potential, it was established that the molecule ZINC2090319 binds strongly to the target related to cardiovascular risk in a desirable way as a non-steroidal antagonist and ZINC408709 binds strongly to the target that is associated with the treatment of inflammatory pathologies and similar to celecoxib. Metabolites generated from these compounds are less likely to have side effects. Simulations were used to evaluate the interaction of compounds with COX-1 and COX-2 during 200 ns. Despite the differences, ZINC408709 molecule showed better stability for COX-2 during molecular dynamics simulation. In the calculations of free energy MM/PBSA, the molecule ZINC408709 ΔGbind value has a higher affinity to celecoxib and rofecoxib COX-2. This demonstrates that the selected substances can be considered as promising COX-2 inhibitors. Communicated by Ramaswamy H. Sarma

Pharmacophore modeling, docking and the integrated use of a ligand- and structure-based virtual screening approach for novel DNA gyrase inhibitors: synthetic and biological evaluation studies.

Fluoroquinolones, a class of compound, act via inhibiting DNA gyrase and topoisomerase IV enzymes. This is an important class of drugs with high success rates for the treatment of tuberculosis and other bacterial infections. An indirect drug design approach was used to develop a meaningful pharmacophore model using the HypoGen module of Discovery Studio 2.0 on a set of 27 structurally diverse compounds with a wide range of biological activity (5 log units). The best hypothesis had three hydrogen bond acceptors (HBA) and one hydrophobic (Hy) moiety, showing r = 0.95, and it predicts the test set of 44 compounds well, with r2 = 0.823. The same features (acceptor and hydrophobic functionality) were validated at the binding site of the DNA gyrase active site using GOLD version 3.0.1 and Molegro Virtual Docker, which showed corresponding hydrogen bond interactions and also π–π stacking interactions that correlated well with the PIC50 values (r2 = 0.6142). The thoroughly validated model was used to screen an extensive database of 0.25 million compounds to identify potential leads. The validated model was implemented for the identification, design, synthesis, and biological evaluation of leads. Ten new chemical entities were synthesized based on our scaffold hopping techniques from the identified virtual screening and tested against the tuberculosis bacterium to obtain preliminary MIC values. The results showed that 3 out of 10 synthesized compounds exhibited good MICs, from 1.25 to 50 μM. This proves the robustness and applicability of the developed model, which is a promising tool for identifying new topoisomerase II inhibitors for the treatment of tuberculosis.

Systematic Structure-Based Virtual Screening Approach to Antibody Selection and Design of a Humanized Antibody against Multiple Addictive Opioids without Affecting Treatment Agents Naloxone and Naltrexone

Opioid drug use, especially heroin, is known as a growing national crisis in America. Heroin itself is a prodrug and is converted to the most active metabolite 6-monoacetylmorphine (6-MAM) responsible for the acute toxicity of heroin and then to a relatively less-active metabolite morphine responsible for the long-term toxicity of heroin. Monoclonal antibodies (mAbs) are recognized as a potentially promising therapeutic approach in the treatment of opioid use disorders (OUDs). Due to the intrinsic challenges of discovering an mAb against multiple ligands, here we describe a general, systematic structure-based virtual screening and design approach which has been used to identify a known anti-morphine antibody 9B1 and a humanized antibody h9B1 capable of binding to multiple addictive opioids (including 6-MAM, morphine, heroin, and hydrocodone) without significant binding with currently available OUD treatment agents naloxone, naltrexone, and buprenorphine. The humanized antibody may serve as a promising candidate for the treatment of OUDs. The experimental binding affinities reasonably correlate with the computationally predicted binding free energies. The experimental activity data strongly support the computational predictions, suggesting that the systematic structure-based virtual screening and humanization design protocol is reliable. The general, systematic structure-based virtual screening and design approach will be useful for many other antibody selection and design efforts in the future.

Design and Optimization of Quinazoline Derivatives: New Non-nucleoside Inhibitors of Bovine Viral Diarrhea Virus.

Bovine viral diarrhea virus (BVDV) belongs to the Pestivirus genus (Flaviviridae). In spite of the availability of vaccines, the virus is still causing substantial financial losses to the livestock industry. In this context, the use of antiviral agents could be an alternative strategy to control and reduce viral infections. The viral RNA-dependent RNA polymerase (RdRp) is essential for the replication of the viral genome and constitutes an attractive target for the identification of antiviral compounds. In a previous work, we have identified potential molecules that dock into an allosteric binding pocket of BVDV RdRp via a structure-based virtual screening approach. One of them, N-(2-morpholinoethyl)-2-phenylquinazolin-4-amine [1, 50% effective concentration (EC50) = 9.7 ± 0.5 μM], was selected to perform different chemical modifications. Among 24 derivatives synthesized, eight of them showed considerable antiviral activity. Molecular modeling of the most active compounds showed that they bind to a pocket located in the fingers and thumb domains in BVDV RdRp, which is different from that identified for other non-nucleoside inhibitors (NNIs) such as thiosemicarbazone (TSC). We selected compound 2-[4-(2-phenylquinazolin-4-yl)piperazin-1-yl]ethanol (1.9; EC50 = 1.7 ± 0.4 μM) for further analysis. Compound 1.9 was found to inhibit the in vitro replication of TSC-resistant BVDV variants, which carry the N264D mutation in the RdRp. In addition, 1.9 presented adequate solubility in different media and a high-stability profile in murine and bovine plasma.

High-throughput virtual screening of novel potent inhibitor(s) for Human Vanin-1 enzyme

Vanin-1 (VNN1) is a glycosylphosphatidylinositol (GPI)-anchored ectoenzyme which hydrolyzes pantetheine to pantothenic acid and cysteamine. It has emerged as a promising drug target for many human diseases associated with oxidative stress and inflammatory pathways. In the present study we used structure-based virtual screening approach for the identification of small molecule inhibitors of vanin-1. A chemical library consisting of natural compounds, synthetic compounds and RRV analogs were screened for drug-like molecules. The filtered molecules were subjected to molecular docking studies. Three potential hits—ZINC04073864 (Natural compound), CID227017 (synthetic compound) and CID129558381 (RRV analog)—were identified for the target enzyme. The molecules form good number of hydrogen bonds with the catalytic residues such as Glu79, Lys178 and Cys211. The apo-VNN1 and VNN1-ligand complexes were subjected to molecular dynamics (MD) simulation for 30 ns. The geometric properties such as root mean square deviation, radius of gyration, solvent accessible surface area, number of hydrogen bonds and the distance between the catalytic triad residues-Glu79, Lys178 and Cys211 were altered upon binding of the compounds. Essential dynamics and entropic studies further confirmed that the fluctuations in VNN1 decrease upon binding of the compounds. The lead molecules were stable throughout the simulation time period. Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) studies showed that Van der Waals interaction energy contributes significantly to the total binding free energy. Thus, our study reveals three lead molecules—ZINC04073864, CID227017 and CID129558381 as potential inhibitors of Vanin-1 which can be validated through further studies. Communicated by Ramaswamy H. Sarma

Virtual screening of phytoconstituents from miracle herb nigella sativa targeting nucleocapsid protein and papain-like protease of SARS-CoV-2 for COVID-19 treatment

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel etiological agent of coronavirus disease 2019 (COVID-19). Nigella sativa, commonly known as black seed or black cumin, has been a historical and traditional plant since thousands of years. Based on their therapeutic efficacy, the chief components of terpenoids and flavonoids were selected from N. sativa seeds and seed oil. This study was designed to check the antiviral efficacy of N. sativa main phytoconstituents against five potential targets of SARS-CoV-2 using in silico structure-based virtual screening approach. Out of twenty five phytocomponents, ten components showed best binding affinity against two viral proteins viz. N-terminal RNA binding domain (NRBD; PDB ID: 6M3M) of nucleocapsid protein and papain-like protease (PL-PRO; PDB ID: 6W9C) of SARS-CoV-2 using AutoDock 4.2.6, AutoDock Vina and iGEMDOCK. PASS analyses of all ten phytocomponents using Lipinski’s Rule of five showed promising results. Further, druglikeness and toxicity assessment using OSIRIS Data Warrior v5.2.1 software exhibited the feasibility of phytocomponents as drug candidates with no predicted toxicity. Molecular dynamics simulation study of NRBD of SARS-CoV-2 nucleocapsid protein-alpha-spinasterol complex and PL-PRO-cycloeucalenol complex displayed strong stability at 300 K. Both these complexes exhibited constant root mean square deviation (RMSDs) of protein side chains and Cα atoms throughout the simulation run time. Interestingly, PL-PRO and NRBD are key proteins in viral replication, host cell immune evasion and viral assembly. Thus, NRBD and PL-PRO have the potential to serve as therapeutic targets for N. sativa phytoconstituents in drug discovery process against COVID-19.

Virtual screening and drug repurposing experiments to identify potential novel selective MAO-B inhibitors for Parkinson's disease treatment.

The main study's purpose is to detect novel natural products (NPs) that are potentially selective MAO-B inhibitors and, additionally, to computationally reposition the marketed drugs with a new therapeutic role for Parkinson's disease. To reach the goals, 3D similarity search, docking, ADMETox, and drug repurposing approaches were employed. Thus, an unbiased benchmarking dataset was built including selective and nonselective inhibitors for MAO-B compliant with both ligand- and structure-based virtual screening approaches. A retrospective and prospective mining scenario was applied to SPECS NP and DrugBank databases to detect novel scaffolds with potential benefits for Parkinson's disease patients. Out of the three best selected natural products, cardamomin showed excellently predicted drug-like properties, superior pharmacological profile, and specific interactions with MAO-B active site, indicating a potential selectivity over MAO-B. Two marketed drugs, fenamisal and monobenzone, were proposed as promising candidates repurposed for Parkinson's disease. The application of shape, physicochemical, and electrostatic similarity searches protocol emerged as a plausible solution to explore MAO-B inhibitors selectivity. This protocol might serve as a rewarding tool in early drug discovery and can be extended to other protein targets.